System and method for anomaly prediction, detection and prevention

A system for anomaly prediction in a plurality of applications of a system to maintain operability of the system, the system comprising:

• a memory;
• and a processor configured to:
• receive real-time data from the plurality of applications, wherein the plurality of applications is at least twenty;
• for each desired variable in the data, determine entropy based on the respective data wherein the entropy can indicate an anomaly in the respective data;
• divide the data for each of the plurality of applications into batches of a fixed size;
• apply a plurality of machine learning models to each of the batches to determine whether the data contains an anomaly or is about to contain an anomaly, wherein the plurality of machine learning models includes a model-based reflex agent and a learning agent that is trained based on historical data from the plurality of applications;
• apply a large language model (LLM) to an output of the plurality of machine learning models to evaluate performance of and fine tune the plurality of machine learning models;
• and transmit an alert to a system that automatically executes one or more scripts to take action to avoid the anomaly.